IROS 2015 论文列表

Stair Climbing is a key functionality desired for robots deployed in Urban Search and Rescue (USAR) scenarios. A novel compliant modular robot was proposed earlier to climb steep and big obstacles. This work extends the functionality of this robot to ascend and descend stairs of dimensions that are also typical of an urban setting. Stair Climbing is realized by equipping the robot's link joints with optimally designed passive spring pairs that resist clockwise and counter clockwise moments generated by the ground during the climbing motion. This 3-module robot is only propelled by wheel actuators. Desirable stair climbing configurations are estimated a-priori and used to obtain the optimal stiffness for springs. Extensive numerical simulation results over different stair configurations are shown. The numerical simulations are corroborated by experimentation using the prototype and its performance is tabulated for different types of surfaces.

Passivity has been the most often used constraint for the controller design of bilateral teleoperation systems. However passivity has been suffering from its own design conservatism since this is a sufficient condition for stability and representing only a small set of overall stability region. In our previous works [1], [2], a less conservatism control approach, we named it Input-to-Sate Stable (ISS) approach, has been introduced for reducing the intrinsic design conservatism of the passivity-based controllers by allowing bigger output energy compared with the passivity-based controller while guaranteeing the stability. However the previous works were limited to haptic interfaces, which is interacting with computer generated virtual environments. In this paper, we extended the ISS approach for bilateral teleoperation systems. For this extension, the previous one-port ISS approach was generalized to two-port ISS approach. The main difficulty of this extension was identifying the signal pair to show hysteresis nonlinear behavior. By introducing a linear function assumption for two-port bilateral controller, which is generally acceptable, we could formulate two-port ISS approach. The extended two-port approach was implemented to a position-force bilateral teleoperation system, and the performance was experimentally verified with a dual Phantom teleoperation system.

The concept of navigating groups of magnetically propelled particles through the fluid-filled passageways of the body provides the potential to perform highly localized diagnostic and therapeutic procedures. The use of MRI scanners to both navigate and propel millimeter-scale robots has received recent attention. MRI-based motion planning and control laws have been proposed that can achieve independent position control of multiple robots despite the system being underactuated, i.e., the same magnetic gradients are experienced by all the robots. To date, however, these analyses have neglected the magnetic interaction forces and torques between these robots. Thus, the question of whether or not the relatively weak gradients can stabilize the particles as they approach each other has remained open. This paper investigates this question by analyzing interaction forces and torques experienced inside an MRI scanner. It is shown that interaction torques can be neglected in the presence of the strong central field of the scanner. Using the reduced force-based model, a lower bound on separation distance is derived and it is shown that this bound could be achieved if the system was fully actuated. Considering underactuation, simulation demonstrates that Model Predictive Control can stabilize pairs of robots at separation distances 2.5-3 times the lower bound on separation distance.

During grasping and other in-hand manipulation tasks maintaining a stable grip on the object is crucial for the task's outcome. Inherently connected to grip stability is the concept of slip. Slip occurs when the contact between the fingertip and the object is partially lost, resulting in sudden undesired changes to the objects state. While several approaches for slip detection have been proposed in the literature, they frequently rely on previous knowledge of the manipulated object. This previous knowledge may be unavailable, seeing that robots operating in real-world scenarios often must interact with previously unseen objects. In our work we explore the generalization capabilities of well known supervised learning methods, using random forest classifiers to create generalizable slip predictors. We utilize these classifiers in the feedback loop of an object stabilization controller. We show that the controller can successfully stabilize previously unknown objects by predicting and counteracting slip events.

Fractional order calculus is a generalization of the familiar integer order calculus in that, it allows for differentiation/integration with orders of any real number. The use of fractional order calculus in systems and control applications provides the user an extra design variable, the order of differointegration, which can be tuned to improve the desired behavior of the overall system. We propose utilization of fractional order models/controllers in haptic systems and study the effect of fractional differentiation order on the stability robustness of the overall sampled-data system. Our results demonstrate that fractional calculus generalization has a significant impact on both the shape and area of stability region of a haptic system and inclusion of fractional order impedances may improve the stability robustness of haptic rendering. Our results also include experimental verification of the stability regions predicted by the theoretical analysis.

Robots made from soft materials have recently captured the interest of researchers from a range of fields including engineers, material scientists, and chemists, biologists, and computer scientists. This new paradigm of soft robotics aims to develop more adaptable, more capable and safer robots that can interact with unstructured environments or permit close cooperation with humans. Current, commercially-available solutions in industrial robotics tend to take a software-centered approach to safe human-robot interaction or focus on the design of lightweight structures consisting of conventional rigid materials. Even though these solutions provide a higher safety level than traditional industrial robots, robots that comprise a sufficiently large amount of soft structures will bring about a certain degree of inherent safety. One of the major challenges in today's soft robotics research is to design robots that are inherently safe and adaptable but are also capable of bearing limited loads. Nature has solved this predicament in larger animals by incorporating stiff endoskeletons, which support the weight of the otherwise predominantly soft bodies. This insight has led to the development of a novel spine-like manipulator (SpineMan) comprised of rigid elements made from polypropylene and soft elements consisting of polyvinyl alcohol (PVA) borax hydrogels that are enveloped in a silicone skin. The initial design, material selection, synthesis, and characterization of this robot are presented in this article.

We developed a system for detecting the speech activity intervals of multiple speakers by combining multiple microphone arrays and human tracking technologies. We also proposed a method for estimating the face orientation of the detected speakers. The developed system was evaluated in two steps: individual utterances in different positions and orientations; and simultaneous dialogues by multiple speakers. Evaluation results revealed that the proposed system could detect speech activity intervals with more than 90% of accuracy, and face orientations with standard deviations within 30 degrees, in situations excluding the cases where all arrays are in the opposite direction to the speaker's face orientation.

In this paper, we present a solution to the Simultaneous Localization and Mapping problem by combining a novel 3D in-air sonar sensor with techniques for estimating the egomotion of a mobile platform (called acoustic flow odometry) and a bio-inspired mapping module (called BatSLAM). This combination eliminates the need for odometric information originating from the robot's motor controller, enabling applications where that information is difficult to obtain, e.g. many electric wheelchairs. The proposed method exploits the programmable spatial sampling capabilities of the 3D sonar system to derive from the same set of received echo signals both an accurate representation of reflectors in the horizontal plane (2D energyscape) and a more coarse representation of reflectors in the frontal hemisphere (3D energyyscape). Using a mapping experiment we demonstrate that the motion estimates originating from the acoustic flow module combined with the coarse frontal hemisphere data provide sufficient information for the mapping module to reconstruct the robot's trajectory.

This paper presents a novel approach to robot audition by performing robotic tasks with auditory cues. Unlike many previous works, we propose a control scheme, that does not require any explicit sound source localization. This approach is capable of controlling all the three degrees of freedom in a plane from two microphones. Built upon the sensor-based control framework, this approach relies on implicit sound source direction obtained from the time difference of arrival (TDOA). We introduce an analytical modelling of auditory cues considering a robot equipped with a pair of microphones and multiple sound sources, from which a control scheme is designed. A stability analysis is provided as well. The results obtained in simulation show the feasibility and the suitability of this method even in reverberant area.

Unmanned solar powered aircraft offer a unique set of advanced capabilities and have set general aviation records for longest continuous flight and greatest sustained altitude. However, the application of solar powered flight to small scale solar powered unmanned aerial vehicles (UAVs) has seen sparse research activity and is only partially explored. The use of solar power as an energy resource allows small scale UAVs to carry heavier, more powerful sensor payloads, and can extend flight times to over 24 hours, thereby achieving multi-day flight. This work focuses on recent developments by the Center for Distributed Robotics on a four meter wingspan solar UAV designed for low altitude aerial sensing applications. Highlighted in this paper are aspects of airframe, propulsion, and electronics hardware design as well as experiments that quantify the solar power system and airframe performance.

We have developed a forceps-type tactile sensor for palpation of a tumor in laparoscopic surgery. The sensor responds to contact position and force at deformable cavity in the sensor probe by using acoustic reflection. The sensor has high applicability for laparoscopic surgery because of its simple structure and disuse of electrical elements within inserted part into patient's body. In this study, we try to measure softness of a contact tissue by using the sensor. Human can estimate softness from contact area and force. Indentation depth is not always required for softness perception. This perception mechanism suggests that our sensor has a possibility for softness measurement because the sensor can respond to contact position and force. Softness measurement contributes to tumor localization and improvement of diseases database. First, the sensor output characteristic is investigated for different soft samples. Then, a method of stiffness measurement using the sensor outputs is proposed. Experimental results show that the sensor has the capability of softness measurement without any additional sensors.

The soft pneumatic actuators (SPAs) are a solution toward the highly customizable and light actuators with the versatility of actuation modes, and an inherent compliance. Such flexibility allows SPAs to be considered as alternative actuators for wearable rehabilitative devices and search and rescue robots. The actuator material and air-chamber design dictate the actuator's mechanical performance. Therefore, each actuator design with a single pressure source produces a highly customized motion but only a single degree of freedom (DoF). We present a novel design and fabrication method for a SPA with different modes of actuation using integrated adjustable stiffness layers (ASLs). Unlike the most SPA designs where one independent chamber is needed for each mode of actuation, here we have a single chamber that drives three different modes of actuation by activating different combinations of ASLs. Adapting customized micro heaters and thermistors for modulating the temperature and stiffness of ASLs, we considerably broaden the work space of the SPA actuator. Here, a thorough characterization of the materials and the modeling of the actuator are presented. We propose a design methodology for developing application specific actuators with multi-DoFs that are light and compact.

As robots enter human spaces, unique perception challenges are emerging. Sensing human activity, adapting to highly dynamic environments, and acting coherently and contingently is challenging when robots transition from structured environments to human-centric ones. We approach this problem by employing context-based perception, a biologically-inspired, low-cost approach to sensing that leverages noisy, global features. Across several months, our mobile robot collected real-world, multimodal data from multi-use locations; where the same space might be used for many different activities. We then ran a series of unimodal and multimodal classification experiments. We successfully classified several aspects of situational context from noisy data, and, to our knowledge are the first group to do so. This work represents an important step toward enabling robots that can readily leverage context to solve perceptual tasks.

The problem of continuous curvature path planning for passages is considered. This problem arises when an autonomous vehicle traverses between prescribed boundaries such as corridors, tunnels, channels, etc. Passage boundaries with curvature and heading discontinuities pose challenges for generating smooth paths passing through them. Continuous curvature half-S shaped paths derived from the Four Parameter Logistic Curve family are proposed as a prospective path planning solution. Analytic conditions are derived for generating continuous curvature paths confined within the passage boundaries. Zero end curvature highlights the scalability of the proposed solution and its compatibility with other path planners in terms of larger path planning domains. Various scenarios with curvature and heading discontinuities are considered presenting viability of the proposed solution.

Many robotics applications require smooth orientation planning, i.e. interpolation or approximation of a frame orientation through prescribed configurations such that the angular velocity and its time derivatives are smooth. This for instance ensures the continuity of the motor torques of robotic manipulator. Yet no satisfactory solution to this problem has been presented. This paper presents a solution using a B-spline parameterization of rotations. The method allows for a continuous interpolation and approximation through a given set of quaternions up to a specified order. The algorithm resembles the well-known B-spline interpolation in the sense that it boils down to solving a system of linear equations. The method is demonstrated for a polishing application (car fender) with an industrial robot.

Percutaneous intervention is a commonly used surgical procedure for many diagnostic and therapeutic operations. Target motion in soft tissue during an intervention caused by tissue deformation is a common problem, along with needle displacement. In this work, we present a deformation planner that generates continuous curvature paths with a bounded curvature derivative that can be used on-line to reach a moving target. This planner is computationally inexpensive and can be used for any robotic system, which has finite angular velocity, to reach a mobile target. The deformation planner, is integrated into a needle steering system using a novel, biologically inspired needle, STING, to track a simulated moving target. In-vitro results in gelatin demonstrate accurate 2D tracking of a moving target (mean 0.27 mm end positional error and 0.80° approach angle error) over 3 target movement rates.

Consumer grade technology seen in cameras and phones has led to the price/performance ratio of sensors and processors falling dramatically over the last decade. In particular, most devices are packaged with a camera, a gyroscope, and an accelerometer, important sensors for aerial robotics. The low mass and small form factor make them particularly well suited for autonomous flight with small flying robots, especially in GPS-denied environments. In this work, we present the first fully autonomous smartphone-based quadrotor. All the computation, sensing and control runs on an off-the-shelf smartphone, with all the software functionality in a smartphone app.We show how quadrotors can be stabilized and controlled to achieve autonomous flight in indoor buildings with application to smart homes, search and rescue, construction and architecture. The work allows any consumer with a smartphone to autonomously drive a quadrotor robot platform, even without GPS, by downloading an app, and concurrently build 3-D maps.

Supervised robotic platforms, able to perform a non-invasive therapy or minimal invasive surgery, represent one of the main achievements in recent years. Robotic-assisted medical procedures with medical doctor, patient and medical assistants interacting with a robotic platform can be seen as a paradigmatic example of the coexistence between system autonomy and human action in medicine. However, this can involve unpredicted and dangerous contacts between robotic structures and humans, contacts that have to be managed with appropriate safety strategies, often embedding specific sensitive components into the robot itself. In this paper, a smart sensorized polymeric skin based on textile multi-touch piezoresistive sensors, able to sense and safely manage pressure exerted during a collision with the surrounding environment (e.g., humans), has been designed, fabricated, integrated on a robotic manipulator and tested. The proposed system shows promising results in managing the pressure exerted during the collision, with a close correlation with the analytical analysis (difference lower than 5.6 kPa - error of 9%).

Recently, many studies have been conducted on soft in-pipe robots, which are expected to work in pipes where ordinary rigid robots cannot work. In this paper, we present a new soft in-pipe locomotive device that consists of six braided tubes. The tubes of the device are inflated by pneumatic power whose inflation drives the device. This device can travel forward and backward and can rotate in both directions in pipes with various diameters with periodic pressurization of the six tubes. We have developed bundled-tube locomotive devices where each device consists of three tubes in which the devices can travel in pipes of various diameters without blocking the flow in the pipes. However these devices cannot control the their rotation in a pipe. Therefore, we developed the new bundled-tube locomotive device that can control the rotation in a pipe. This new device is a braid with six tubes that include a right-hand helix and a left-hand helix with three tubes each. The developed braided device can achieve various motions based on the pressurization patterns in each of the six tubes. In this paper, we thoroughly explain the relationship between the motions of the device and the pressurization pattern. We also present the locomotion experiment within a pipe with a variable-diameter part and a part that bends in an elbow shape.